MixingBoard: a Knowledgeable Stylized Integrated Text Generation Platform
May 17, 2020 ยท Declared Dead ยท ๐ Annual Meeting of the Association for Computational Linguistics
"No code URL or promise found in abstract"
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Authors
Xiang Gao, Michel Galley, Bill Dolan
arXiv ID
2005.08365
Category
cs.CL: Computation & Language
Citations
6
Venue
Annual Meeting of the Association for Computational Linguistics
Last Checked
4 months ago
Abstract
We present MixingBoard, a platform for quickly building demos with a focus on knowledge grounded stylized text generation. We unify existing text generation algorithms in a shared codebase and further adapt earlier algorithms for constrained generation. To borrow advantages from different models, we implement strategies for cross-model integration, from the token probability level to the latent space level. An interface to external knowledge is provided via a module that retrieves on-the-fly relevant knowledge from passages on the web or any document collection. A user interface for local development, remote webpage access, and a RESTful API are provided to make it simple for users to build their own demos.
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